# Genetic algorithms and simulated annealing: a marriage proposal

@article{Adler1993GeneticAA, title={Genetic algorithms and simulated annealing: a marriage proposal}, author={Daniel Adler}, journal={IEEE International Conference on Neural Networks}, year={1993}, pages={1104-1109 vol.2} }

Genetic algorithms (GAs) and simulated annealing (SA) have emerged as the leading methodologies for search and optimization problems in high dimensional spaces. [...] Key Method The implementation of this algorithm within an existing GA environment is shown to be trivial, allowing the system to operate as pure SA (or iterated SA), pure GA, or in various hybrid modes. The performance of the algorithm is tested on various large-scale applications, including DeJong's functions, a 100-city traveling-salesmanâ€¦ Expand

#### Tables and Topics from this paper

#### 104 Citations

Improving real-parameter genetic algorithm with simulated annealing for engineering problems

- Engineering, Computer Science
- Adv. Eng. Softw.
- 2006

A novel adaptive real-parameter simulatedAnnealing genetic algorithm (ARSAGA) that maintains the merits of genetic algorithm and simulated annealing and adaptive mechanisms are added to insure the solution quality and to improve the convergence speed. Expand

A hybrid real-parameter genetic algorithm for function optimization

- Computer Science
- Adv. Eng. Informatics
- 2006

The results indicate that the global searching ability and the convergence speed of this novel hybrid algorithm are significantly better, even though small population size is used, and the proposed algorithm has good application to engineering optimization problems. Expand

Adaptive simulated annealing genetic algorithm for control applications

- Computer Science
- Int. J. Syst. Sci.
- 1996

An efficient hybrid genetic algorithm named the adaptive simulated annealing genetic algorithm (ASAGA) which is used in control applications and illustrated by simulation examples for system identification and control that include neural networks which are particularly suitable for applications of ASAGA. Expand

Adaptive simulated annealing genetic algorithm for system identification

- Computer Science
- 1996

An efficient hybrid algorithm named ASAGA (Adaptive Simulated Annealing Genetic Algorithm) is proposed, by introducing a mutation operator like simulated annealing and an adaptive cooling schedule to produce an adaptive algorithm that has the merits of both genetic algorithms and simulatedAnnealing. Expand

Simulated annealing based on local genetic search

- Computer Science
- 2009 IEEE Congress on Evolutionary Computation
- 2009

An innovative model recently proposed, which performs local search on external solutions, is extended to match search process carried out by simulated annealing, and acceptance criterion and cooling scheme concepts from simulatedAnnealing are introduced. Expand

Hybrid Genetic-simulated Annealing Algorithm for Optimal Weapon Allocation in Multilayer Defence Scenario

- Engineering
- 2004

Simulated annealing is one of the several heuristic optimisation techniques, that has been studied in the past to determine the most effective mix of weapons and their allocation to enemytargets in aâ€¦ Expand

A genetic algorithm-based approach to flexible flow-line scheduling with variable lot sizes

- Mathematics, Medicine
- IEEE Trans. Syst. Man Cybern. Part B
- 1997

This work presents a novel approach for solving two related problems-lot sizing and sequencing-concurrently using GAs by using a unified representation for the information about both the lot sizes and the sequence and enabling GAs to evolve the chromosome by replacing primitive genes with good building blocks. Expand

A Hybrid Genetic Algorithm with Boltzmann Convergence Properties

- Mathematics
- 2008

Abstract
Stochastic global search algorithms such as genetic algorithms are used to attack difficult combinatorial optimization problems. However, genetic algorithms suffer from the lack of aâ€¦ Expand

Engineering optimization using a real-parameter genetic-algorithm-based hybrid method

- Computer Science
- 2006

A hybrid optimization algorithm which combines the respective merits of the genetic algorithm and the simulated annealing algorithm and incorporates adaptive mechanisms designed to adjust the probabilities of the cross-over and mutation operators such that its hill-climbing ability towards the optimum solution is improved. Expand

Blending Roulette Wheel Selection & Rank Selection in Genetic Algorithms

- Computer Science
- 2012

A blended selection operator is proposed that is a perfect mix of both exploration and exploitation in genetic algorithms and the results were compared with roulette wheel selection and rank selection with different problem sizes. Expand

#### References

SHOWING 1-10 OF 20 REFERENCES

Stochastic iterated genetic hillclimbing

- Mathematics
- 1987

In the "black box function optimization" problem, a search strategy is required to find an extremal point of a function without knowing the structure of the function or the range of possible functionâ€¦ Expand

Adapting Operator Probabilities in Genetic Algorithms

- Computer Science
- ICGA
- 1989

This dissertation describes an empirical investigation into whether it can be convincingly argued that these probabilities should vary over the course of a genetic algorithm run so as to account for changes in the ability of the operators to produce children of increased strength. Expand

Handbook Of Genetic Algorithms

- Computer Science
- 1990

This book sets out to explain what genetic algorithms are and how they can be used to solve real-world problems, and introduces the fundamental genetic algorithm (GA), and shows how the basic technique may be applied to a very simple numerical optimisation problem. Expand

the utility of using the genetic algorithm approach on the problem of Davis, L. (1991), Handbook of Genetic Algorithms. Van Nostrand Reinhold, New York.

- Computer Science
- 1991

The complex effect of genetic algorithm's (GA) operators and parameters to Davis (7) proposed a method that would make the operators evolve or adapt to the problem as Handbook of Genetic Algorithms.â€¦ Expand

Neighborhood size in the Simulated Annealing Algorithm

- Mathematics
- 1988

SYNOPTIC ABSTRACTSimulated annealing is a probabilistic algorithm that has shown some promise when applied to combinatorially NP-hard problems. One advantage of the simulated annealing algorithm isâ€¦ Expand

Genetic Algorithms in Search Optimization and Machine Learning

- Computer Science
- 1988

This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields. Expand

Simulated Annealing and Combinatorial Optimization

- Computer Science
- DAC 1986
- 1986

The issues involved in using an adaptive heuristic in general, and simulated annealing, probabilistic hill climbing, and sequence heuristics in particular are exposed. Expand

The CHC Adaptive Search Algorithm: How to Have Safe Search When Engaging in Nontraditional Genetic Recombination

- Computer Science
- FOGA
- 1990

Abstract This paper describes and analyzes CHC, a nontraditional genetic algorithm which combines a conservative selection strategy that always preserves the best individuals found so far with aâ€¦ Expand

Adaptation in natural and artificial systems

- Computer Science
- 1975

Names of founding work in the area of Adaptation and modiication, which aims to mimic biological optimization, and some (Non-GA) branches of AI. Expand

Simulated, simulated annealing

- Computer Science
- 1988

This work presents a few â€śswindlingâ€ť ideas for speeding up SA by simulating its action on a problem by increasing speed at the cost of decreasing generality. Expand